31 May
2021
31 May
'21
7:34 p.m.
On the longer term solution I'd definitely go with decoupling the
server-client mgr API with something like HTTP+JSON, gRPC, ...
On the shorter term front:
It seems that Python 3.10 (to be released later this year) will
(experimentally) feature something called "isolated subinterpreters"
<https://vstinner.github.io/isolate-subinterpreters.html>. That said, its
list of caveats definitely keeps it far away from production readiness
(e.g.: GC and many optimizations disabled).
However, there's an interesting note there: the way it does for
instantiating modules, multi-phase initialization (PEP 489), is available
since Python 3.5 <https://www.python.org/dev/peps/pep-0489/>. While module
globals are not fully isolated, it seems that at least it's adding
some improved
isolation compared to the regular shallow copy of the PyModule_Create()
<https://docs.python.org/3/c-api/init.html#c.Py_NewInterpreter>.
Another (lazy/desperate) alternative might be trying to import numpy from
the main/global interpreter and seeing if that improves the situation?
Kind Regards,
Ernesto
On Mon, May 31, 2021 at 11:37 AM Sebastian Wagner <sewagner(a)redhat.com>
wrote:
Am 28.05.21 um 05:01 schrieb kefu chai:
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On Thu, May 27, 2021 at 9:58 PM John Spray
<jcspray(a)gmail.com> wrote:
> Hey,
>
> Hope you don't mind me chiming in, as someone responsible for some of
the
mess :-)
Hi John, thanks for your reply! Nice to see you here.
> Testing my memory a bit but...
sub-interpreters were originally used
because some badly behaved dependencies (I
think it was one of the web
server libraries?) used global mutable state on their own module, and
thereby caused a problem if two mgr modules were both using that dependency.
Right, except that this doesn't help with global mutable state in native
modules, like numpy.
> Using sub-interpreters put us on the fringes
of CPython use cases,
which isn't a great place to be. The other option is to
use separate
processes rather than multiple interpreters in the same process. At the
time, that seemed too expensive (in terms of developer time), although
process separation would be the preferable level of separation for
functionally distinct units.
>
> Some thoughts on options:
> A) Isolate modules in processes, tethered to a central ceph-mgr process
that
provides a new RPC interface that mimics the existing MgrModule
interface. Lots of work. Will introduce substantial runtime overhead.
>
> B) Isolate modules in processes, where each is a first class RADOS
client --
basically run N ceph-mgr daemons, each hosting a particular
module (or group of modules, to reduce overhead for tiny modules). Much
less work, but would need careful design to avoid adding user-facing
complexity in managing many daemons.
That sounds complicated for non-containerized deployments. For Rook and
cephadm, this should be doable.
>
> C) Look at alternate python interpreters that might provide cleaner
sandboxing
than CPython (I am not up to date on the python world but
perhaps something exists).
in future, probably we could compile the python
modules into web
assembly modules and run them in a different interpreter which can be
retargeted to Wasm. so we can write the mgr modules in languages like
Scheme and Rust!
Good luck compiling native Python modules to web assembly :-P .
Seriously, we'd loose a lot of compatibility with the Python ecosystem.
> D) Stop using sub-interpreters, and forbid
any python dependencies that
use global state that could conflict between modules.
Basically any time
two modules use the same dependency, it needs some level of audit to ensure
they aren't going to collide.
i think this might be a more promising solution.
but probably we need
to understand which dependency was using global mutable, and made us
use sub-interpreters. and how. was it cherrypy? it is used by restful
and dashboard. and seems it was causing troubles. see
https://github.com/ceph/ceph/pull/14971
Maybe we could think of having a shared cherrypy instance that delegates
request handling with WSGI.
> E) Re-write problematic mgr modules to C++. Perhaps if a module is
numerically intensive enough to need numpy then it might be better off as
native code to begin with. C++ with all the modern features is even quite
a nice language :-)
The dependency chain looks like so: mgr/rook -> kubernetes -> websocket
-> numpy. I'd like to avoid rewriting mgr/rook in C++ :-)
>
> Sorry for the wall of text, hope that's some help.
>
> John
>
>
>
>
>
>
>
>
>
> On Wed, May 26, 2021 at 1:56 PM Sebastian Wagner <sewagner(a)redhat.com>
wrote:
>> All,
>>
>>
>> We have two issues:
>>
>> * https://tracker.ceph.com/issues/45574
>> * https://tracker.ceph.com/issues/48787
>>
>> Caused by numpy not supporting Python sub-interpreters. Unfortunately,
the
latter issue came up in the most recent Octopus
validations. I suspect
it's just
a matter of time, till our users are affected by it.
Note that removing numpy is not easy, as kuberenetes-client depends
(transitively) on numpy.
Thoughts?
- Sebastan
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